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Record W2123578898 · doi:10.1109/tdmr.2005.859576

Numerical modeling of pacemaker interference in the electric-utility environment

2005· article· en· W2123578898 on OpenAlexaff
M.A. Stuchly, Robert Kavet

Bibliographic record

VenueIEEE Transactions on Device and Materials Reliability · 2005
Typearticle
Languageen
FieldEngineering
TopicElectrostatic Discharge in Electronics
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsEMIElectromagnetic interferenceElectric fieldElectrostatic dischargeInterference (communication)Electromagnetic compatibilityElectric potentialElectrical engineeringCardiac pacemakerElectronic engineeringMaterials scienceEngineeringVoltagePhysicsMedicineCardiology

Abstract

fetched live from OpenAlex

Potential for electromagnetic interference (EMI) with cardiac pacemakers in workplaces in electric utilities due to 50- and 60-Hz fields is well known. Only younger employees of electric-utility companies may want to return to their jobs that often entail exposure to such fields. EMI may occur due to exposure to strong external electric fields, magnetic fields, contact currents, and electrostatic discharges (ESD). Numerical modeling of the potential differences produced between the pacemaker electrodes in situ, i.e., in the heterogeneous model of a human body, allows for the evaluation of potential EMI prior to an implantation of the device. Such modeling has been performed and the results are presented and compared for different conditions of potential EMI. As expected, unipolar pacemakers are more susceptible than bipolar devices.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.224
Teacher spread0.213 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2005
Admission routes1
Has abstractyes

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Same venueIEEE Transactions on Device and Materials ReliabilitySame topicElectrostatic Discharge in ElectronicsFrench-language works237,207